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Proceedings Paper

Unsupervised automated panorama creation for realistic surveillance scenes through weighted mutual information registration
Author(s): Thomas P. Keane; Eli Saber; Harvey Rhody; Andreas Savakis; Jeffrey Raj
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Paper Abstract

Automated panorama creation usually requires camera calibration or extensive knowledge of camera locations and relations to each other. Registration problems are often solved by these same camera parameters or the result of complex point matching schemes. This paper presents a novel automated panorama creation algorithm by using an affine transformation search based on maximized mutual information (MMI). MMI techniques are often limited to airborne and satellite imagery or medical images, but we can show that a simple MMI algorithm very well approximates realistic scenes of varying depth distortion. This study was performed on stationary color surveillance video cameras and proves extremely worthwhile in any system with limited or no a priori camera-to-camera parameters. This algorithm is quite robust on a very large range of strict- to nearly-affine related scenes, and provides a great approximation for the overlap regions in scenes related by a projective homography. Practical considerations were surprisingly significant in molding the development of this robust and versatile algorithm.

Paper Details

Date Published: 3 February 2011
PDF: 9 pages
Proc. SPIE 7870, Image Processing: Algorithms and Systems IX, 78700T (3 February 2011); doi: 10.1117/12.872161
Show Author Affiliations
Thomas P. Keane, Rochester Institute of Technology (United States)
Eli Saber, Rochester Institute of Technology (United States)
Harvey Rhody, Rochester Institute of Technology (United States)
Andreas Savakis, Rochester Institute of Technology (United States)
Jeffrey Raj, Lenel Systems International Inc. (United States)


Published in SPIE Proceedings Vol. 7870:
Image Processing: Algorithms and Systems IX
Jaakko T. Astola; Karen O. Egiazarian, Editor(s)

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